Data from: Sexual selection is ineffectual or inhibits the purging of deleterious mutations in Drosophila melanogaster
Bibliographic record
Abstract
The effects of sexual selection on population mean fitness are unclear and a subject of debate. Recent models propose that, because reproductive success may be condition-dependent, much of the genome may be a target of sexual selection. Under this scenario, mutations that reduce health, and thus non-sexual fitness, may also be deleterious with respect to reproductive success, meaning that sexual selection may contribute to the purging of deleterious alleles. We tested this hypothesis directly by subjecting replicate Drosophila melanogaster populations to two treatments that altered the opportunity for sexual selection and then tracked changes in the frequency of six separate deleterious alleles with recessive and visible phenotypic effects. While natural selection acted to decrease the frequency of all six mutations, the addition of sexual selection did not aid in the purging of any of them, and for three of them appears to have hampered it. Courtship and mating have harmful effects in this species and mate choice assays showed that males directed more courtship and mating behavior towards wild-type over mutant females, providing a likely explanation for sexual selection’s cost. Whether this cost extends to other mutations (e.g., those lacking visible phenotypic effects) is an important topic for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".